Search Results - (( java implication based algorithm ) OR ( knowledge using clustering algorithm ))

Search alternatives:

Refine Results
  1. 1
    Document clustering for knowledge discovery using nature-inspired algorithm

    Document clustering for knowledge discovery using nature-inspired algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2014
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  2. 2
    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients

    The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Consequently, the implementation of z-numbers in fuzzy clustering algorithm is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in uncertain information development. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  3. 3
    Reliability fuzzy clustering algorithm for wellness of elderly people

    Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

    Published 2019
    “…Thus, the objective of this paper is to propose a reliable fuzzy clustering algorithm using z-numbers. This model will demonstrate the capability to handle the knowledge of human being and uncertain information in evaluating the wellness of chronic kidney disease (CKD) patients. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  4. 4
    Optimizing the Management of Knowledge Assets using Swarm Intelligence

    Optimizing the Management of Knowledge Assets using Swarm Intelligence by Yusof, Yuhanis, Baharom, Fauziah, Mohamed, Athraa Jasim

    Published 2018
    “…Hence, the produced clusters will be of different quality. This study presents the employment of swarm intelligence algorithm, i.e Firefly Algorithm, to automatically cluster text document without the use of k value. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  5. 5
    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization

    Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

    Published 2024
    thesis::doctoral thesis
    Save to List
    Saved in:
  6. 6
    Clustering for binary data sets by using genetic algorithm-incremental K-means

    Clustering for binary data sets by using genetic algorithm-incremental K-means by Saharan, S., Baragona, R., Nor, M. E., Salleh, R. M., Asrah, N. M.

    Published 2018
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    A study of density-grid based clustering algorithms on data streams

    A study of density-grid based clustering algorithms on data streams by Amini, A., Saybani, M.R., Sahaf Yazdi, S.R.A.

    Published 2011
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  8. 8
    Clustering chemical data set using particle swarm optimization based algorithm

    Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

    Published 2008
    “…Many algorithms had been applied to cluster chemical data set such as Ward’s algorithm. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Adaptive firefly algorithm for hierarchical text clustering

    Adaptive firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim

    Published 2016
    “…The proposed Adaptive Firefly Algorithm (AFA) consists of three components: document clustering, cluster refining, and cluster merging. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  10. 10
    Automatic clustering of gene ontology by genetic algorithm

    Automatic clustering of gene ontology by genetic algorithm by Othman, Razib M., Deris, Safaai, Zakaria, Zalmiyah, Illias, Rosli M., Mohamad, Saberi M.

    Published 2006
    “…Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Comparison of clustering algorithms on air quality substances in Peninsular Malaysia / Sitti Sufiah Atirah Rosly, Balkiah Moktar and Muhamad Hasbullah Mohd Razali

    Comparison of clustering algorithms on air quality substances in Peninsular Malaysia / Sitti Sufiah Atirah Rosly, Balkiah Moktar and Muhamad Hasbullah Mohd Razali by Rosly, Sitti Sufiah Atirah, Moktar, Balkiah, Mohd Razali, Muhamad Hasbullah

    Published 2017
    “…Monthly data from 37 monitoring stations in Peninsular Malaysia from the year 2013 to 2015 were used in this study. K-Means (KM) clustering algorithm, Expectation Maximization (EM) clustering algorithm and Density Based (DB) clustering algorithm have been chosen as the techniques to analyze the cluster analysis by utilizing the Waikato Environment for Knowledge Analysis (WEKA) tools. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    On density-based data streams clustering algorithms: A survey

    On density-based data streams clustering algorithms: A survey by Teh, Y.W.

    Published 2017
    “…Moreover, we investigate the evaluation metrics used in validating cluster quality and measuring algorithms’ performance. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  13. 13
    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data

    MGR: An Information Theory Based Hierarchical Divisive Clustering Algorithm for Categorical Data by Hongwu, Qin, Ma, Xiuqin, Herawan, Tutut, Jasni, Mohamad Zain

    Published 2014
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    Efficient genetic partitioning-around-medoid algorithm for clustering

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…Accordingly, the corresponding genetic operators are adapted to suite the medoid and to incorporate much clustering-specific domain knowledge. The algorithm is also preceded with careful seeding using mathematically proved to converge k-means++ algorithm. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mohammad Ramly and Nor Hasliza Saberi

    Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mo... by Ruslan, Mohammad Adha, Mohammad Ramly, Nurul Shahira, Saberi, Nor Hasliza

    Published 2019
    “…The main purpose of this study are to compare the knowledge discovery between Market Basket Analysis and Partition Around Medoids and followed by to generate a customer buying pattern by using Market Basket Analysis (MBA) Algorithm and Partition Around Medoids (PAM) Clustering Algorithm. …”
    Get full text
    Get full text
    Student Project
    Save to List
    Saved in:
  16. 16
    An adaptive density-based method for clustering evolving data streams / Amineh Amini

    An adaptive density-based method for clustering evolving data streams / Amineh Amini by Amini, Amineh

    Published 2014
    “…Density-based method has emerged as a worthwhile class for clustering data streams. It has the abilities to discover clusters of arbitrary shapes, handle noise, and cluster without prior knowledge of number of clusters. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Determining number of clusters using firefly algorithm with cluster merging for text clustering

    Determining number of clusters using firefly algorithm with cluster merging for text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection.In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced.The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. …”
    Get full text
    Get full text
    Book Section
    Save to List
    Saved in:
  18. 18
    Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification

    Cluster identification and separation in the growing self-organizing map: Application in protein sequence classification by Ahmad, N.

    Published 2010
    “…Therefore, the aim of this paper is to investigate the effect of the spread factor value towards cluster separation in the GSOM. We used simple k-means algorithm as a method to identify clusters in the GSOM. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar

    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

    Published 2016
    “…This unsupervised learning usually leads to undirected knowledge discovery. The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering

    Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering by Rahmah, Mokhtar, Raza, Muhammad Ahsan, Fauziah, Zainuddin, Nor Azhar, Ahmad, Raza, Muhammad Fahad, Raza, Binish

    Published 2021
    “…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: